<?xml version="1.0" encoding="UTF-8"?>
<metabolite>
  <version>1.0</version>
  <creation_date>2016-09-30 22:19:49 UTC</creation_date>
  <update_date>2020-06-04 21:34:49 UTC</update_date>
  <accession>BMDB0000122</accession>
  <secondary_accessions>
    <accession>BMDB00122</accession>
  </secondary_accessions>
  <name>D-Glucose</name>
  <description>D-Glucose, also known as D-GLC or cerelose, belongs to the class of organic compounds known as hexoses. These are monosaccharides in which the sugar unit is a is a six-carbon containing moeity. D-Glucose exists as a solid, possibly soluble (in water), and an extremely weak basic (essentially neutral) compound (based on its pKa) molecule. D-Glucose exists in all living species, ranging from bacteria to humans. In cattle, D-glucose is involved in the metabolic pathway called the starch and sucrose metabolism pathway. D-Glucose is a potentially toxic compound. D-Glucose has been found to be associated with several diseases known as hypoglycemia, familial neonatal, donohue syndrome, and pregnancy; also d-glucose has been linked to several inborn metabolic disorders including 3-methyl-crotonyl-glycinuria and growth hormone deficiency.</description>
  <synonyms>
    <synonym>D-GLC</synonym>
    <synonym>D-GLCP</synonym>
    <synonym>Dextrose</synonym>
    <synonym>GLC-OH</synonym>
    <synonym>Glucose</synonym>
    <synonym>Grape sugar</synonym>
    <synonym>WURCS=2.0/1,1,0/[a2122h-1x_1-5]/1/</synonym>
    <synonym>Purified glucose</synonym>
    <synonym>D-Glucopyranose</synonym>
    <synonym>Roferose ST</synonym>
    <synonym>(+)-Glucose</synonym>
    <synonym>Anhydrous dextrose</synonym>
    <synonym>Cerelose</synonym>
    <synonym>Cerelose 2001</synonym>
    <synonym>Clearsweet 95</synonym>
    <synonym>Clintose L</synonym>
    <synonym>Corn sugar</synonym>
    <synonym>CPC Hydrate</synonym>
    <synonym>D(+)-Glucose</synonym>
    <synonym>Dextropur</synonym>
    <synonym>Dextrosol</synonym>
    <synonym>Glucodin</synonym>
    <synonym>Glucolin</synonym>
    <synonym>Goldsugar</synonym>
    <synonym>Meritose</synonym>
    <synonym>Staleydex 111</synonym>
    <synonym>Staleydex 95m</synonym>
    <synonym>Tabfine 097(HS)</synonym>
    <synonym>Vadex</synonym>
    <synonym>D Glucose</synonym>
    <synonym>Glucose, (DL)-isomer</synonym>
    <synonym>Glucose, (L)-isomer</synonym>
    <synonym>Glucose, (beta-D)-isomer</synonym>
    <synonym>Glucose monohydrate</synonym>
    <synonym>Glucose, (alpha-D)-isomer</synonym>
    <synonym>L Glucose</synonym>
    <synonym>L-Glucose</synonym>
    <synonym>Dextrose, anhydrous</synonym>
    <synonym>Monohydrate, glucose</synonym>
  </synonyms>
  <chemical_formula>C6H12O6</chemical_formula>
  <average_molecular_weight>180.1559</average_molecular_weight>
  <monisotopic_moleculate_weight>180.063388116</monisotopic_moleculate_weight>
  <iupac_name>(3R,4S,5S,6R)-6-(hydroxymethyl)oxane-2,3,4,5-tetrol</iupac_name>
  <traditional_iupac>glucose</traditional_iupac>
  <cas_registry_number>2280-44-6</cas_registry_number>
  <smiles>[H]C1(O)O[C@]([H])(CO)[C@@]([H])(O)[C@]([H])(O)[C@@]1([H])O</smiles>
  <inchi>InChI=1S/C6H12O6/c7-1-2-3(8)4(9)5(10)6(11)12-2/h2-11H,1H2/t2-,3-,4+,5-,6?/m1/s1</inchi>
  <inchikey>WQZGKKKJIJFFOK-GASJEMHNSA-N</inchikey>
  <taxonomy>
    <description> belongs to the class of organic compounds known as hexoses. These are monosaccharides in which the sugar unit is a is a six-carbon containing moeity.</description>
    <kingdom>Organic compounds</kingdom>
    <super_class>Organic oxygen compounds</super_class>
    <class>Organooxygen compounds</class>
    <sub_class>Carbohydrates and carbohydrate conjugates</sub_class>
    <direct_parent>Hexoses</direct_parent>
    <alternative_parents>
      <alternative_parent>Hemiacetals</alternative_parent>
      <alternative_parent>Hydrocarbon derivatives</alternative_parent>
      <alternative_parent>Oxacyclic compounds</alternative_parent>
      <alternative_parent>Oxanes</alternative_parent>
      <alternative_parent>Polyols</alternative_parent>
      <alternative_parent>Primary alcohols</alternative_parent>
      <alternative_parent>Secondary alcohols</alternative_parent>
    </alternative_parents>
    <substituents>
      <substituent>Alcohol</substituent>
      <substituent>Aliphatic heteromonocyclic compound</substituent>
      <substituent>Hemiacetal</substituent>
      <substituent>Hexose monosaccharide</substituent>
      <substituent>Hydrocarbon derivative</substituent>
      <substituent>Organoheterocyclic compound</substituent>
      <substituent>Oxacycle</substituent>
      <substituent>Oxane</substituent>
      <substituent>Polyol</substituent>
      <substituent>Primary alcohol</substituent>
      <substituent>Secondary alcohol</substituent>
    </substituents>
    <molecular_framework>Aliphatic heteromonocyclic compounds</molecular_framework>
    <external_descriptors>
      <external_descriptor>Aldoses</external_descriptor>
      <external_descriptor>D-glucose</external_descriptor>
      <external_descriptor>glucopyranose</external_descriptor>
    </external_descriptors>
  </taxonomy>
  <experimental_properties>
    <state>Solid</state>
    <property>
      <kind>melting_point</kind>
      <value>146 - 150 °C</value>
      <source/>
    </property>
    <property>
      <kind>water_solubility</kind>
      <value>1200.0 mg/mL</value>
      <source/>
    </property>
    <property>
      <kind>logp</kind>
      <value>-3.24</value>
      <source>SANGSTER (1994)</source>
    </property>
  </experimental_properties>
  <predicted_properties>
    <property>
      <kind>logp</kind>
      <value>-2.57</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logs</kind>
      <value>0.64</value>
      <source>ALOGPS</source>
    </property>
    <property>
      <kind>logp</kind>
      <value>-2.9</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>pka_strongest_acidic</kind>
      <value>11.3</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>pka_strongest_basic</kind>
      <value>-3</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>iupac</kind>
      <value>(3R,4S,5S,6R)-6-(hydroxymethyl)oxane-2,3,4,5-tetrol</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>average_mass</kind>
      <value>180.1559</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>mono_mass</kind>
      <value>180.063388116</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>smiles</kind>
      <value>[H]C1(O)O[C@]([H])(CO)[C@@]([H])(O)[C@]([H])(O)[C@@]1([H])O</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>formula</kind>
      <value>C6H12O6</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchi</kind>
      <value>InChI=1S/C6H12O6/c7-1-2-3(8)4(9)5(10)6(11)12-2/h2-11H,1H2/t2-,3-,4+,5-,6?/m1/s1</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>inchikey</kind>
      <value>WQZGKKKJIJFFOK-GASJEMHNSA-N</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polar_surface_area</kind>
      <value>110.38</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>refractivity</kind>
      <value>35.92</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>polarizability</kind>
      <value>16.37</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>rotatable_bond_count</kind>
      <value>1</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>acceptor_count</kind>
      <value>6</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>donor_count</kind>
      <value>5</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>physiological_charge</kind>
      <value>0</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>formal_charge</kind>
      <value>0</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>number_of_rings</kind>
      <value>1</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>bioavailability</kind>
      <value>1</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>rule_of_five</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>ghose_filter</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>veber_rule</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
    <property>
      <kind>mddr_like_rule</kind>
      <value>Yes</value>
      <source>ChemAxon</source>
    </property>
  </predicted_properties>
  <pathways>
    <pathway>
      <name>Galactose Metabolism</name>
      <smpdb_id>SMP0087225</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Gluconeogenesis</name>
      <smpdb_id>SMP0087223</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Glucose-Alanine Cycle</name>
      <smpdb_id>SMP0087221</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Glycolysis</name>
      <smpdb_id>SMP0087222</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Growth Hormone Signaling Pathway </name>
      <smpdb_id>SMP0120923</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Insulin Signalling</name>
      <smpdb_id>SMP0108189</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Lactose Degradation</name>
      <smpdb_id>SMP0087253</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Lactose Synthesis</name>
      <smpdb_id>SMP0087229</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Pancreas Function</name>
      <smpdb_id>SMP0119380</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Transfer of Acetyl Groups into Mitochondria</name>
      <smpdb_id>SMP0087254</smpdb_id>
      <kegg_map_id/>
    </pathway>
    <pathway>
      <name>Warburg Effect</name>
      <smpdb_id>SMP0087270</smpdb_id>
      <kegg_map_id/>
    </pathway>
  </pathways>
  <spectra>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>1093</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrOneD</type>
      <spectrum_id>1152</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>334</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>335</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>336</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>337</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1428</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1598</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1601</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1632</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>1707</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>2406</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30344</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30345</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30766</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>30767</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31005</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31006</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31007</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31008</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>31009</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::CMs</type>
      <spectrum_id>37304</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::NmrTwoD</type>
      <spectrum_id>1151</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>177</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>179</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2913</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2914</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2915</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2916</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>2917</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178080</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178081</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>178082</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>180393</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>180394</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>180395</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>437657</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>437658</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>437659</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>437660</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>437661</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3609526</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3609527</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3609528</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3610429</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3610430</spectrum_id>
    </spectrum>
    <spectrum>
      <type>Specdb::MsMs</type>
      <spectrum_id>3610431</spectrum_id>
    </spectrum>
  </spectra>
  <normal_concentrations>
    <concentration>
      <biospecimen>Adipose Tissue</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Adrenal Cortex</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Adrenal Gland</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Adrenal Medulla</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Bladder</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR</comment>
      <references>
        <reference>
          <reference_text>Tian H, Wang W, Zheng N, Cheng J, Li S, Zhang Y, Wang J: Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows. J Proteomics. 2015 Jul 1;125:17-28. doi: 10.1016/j.jprot.2015.04.014. Epub 2015 Apr 22.</reference_text>
          <pubmed_id>25913299</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>2941.896 +/- 253.114</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by Spectrometry (Autoanalyzer/BT3000 Plus)</comment>
      <references>
        <reference>
          <reference_text>Abdullah BASOGLU, Nuri BASPINAR, Alparslan COSKUN. NMR-based metabolomic evaluation in dairy cows with displaced abomasum. Turk J Vet Anim Sci (2014) 38(3):325-330</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>5550</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by Dacos Chemistry Analyzer in Hereford cows</comment>
      <references>
        <reference>
          <reference_text>Early RJ, McBride BW, Ball RO: Growth and metabolism in somatotropin-treated steers: I. Growth, serum chemistry and carcass weights. J Anim Sci. 1990 Dec;68(12):4134-43. doi: 10.2527/1990.68124134x.</reference_text>
          <pubmed_id>2286555</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Jiyuan Li, Everestus C. Akanno, Tiago Valente, Mohammed Abo-Ismail, Brian Karisa, Zhiquan Wang, Graham S. Plastow.  Genomic heritability and genome-wide association studies of plasma metabolites in crossbred beef cattle. (in preparation)</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by LC-MS and NMR in Angus-Hereford cows.</comment>
      <references>
        <reference>
          <reference_text>Aich P, Babiuk LA, Potter AA, Griebel P: Biomarkers for prediction of bovine respiratory disease outcome. OMICS. 2009 Jun;13(3):199-209. doi: 10.1089/omi.2009.0012.</reference_text>
          <pubmed_id>19275474</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>3840-4610</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Cobas c311 chemistry analyzer</comment>
      <references>
        <reference>
          <reference_text>Consolo NRB, Munro JC, Bourgon SL, Karrow NA, Fredeen AH, Martell JE, Montanholi YR: Associations of Blood Analysis with Feed Efficiency and Developmental Stage in Grass-Fed Beef Heifers. Animals (Basel). 2018 Aug 2;8(8). pii: ani8080133. doi: 10.3390/ani8080133.</reference_text>
          <pubmed_id>30072590</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>4196.365 +/- 505.118</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by Trinder (1969) method</comment>
      <references>
        <reference>
          <reference_text>C. R. E. Cogginsa and A. C. Field. Diurnal variation in the chemical composition of plasma from lactating beef cows on three dietary energy intakes. J. agric. Sri., Camb. (1976), 86, 595-602</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>2800-4600</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Randox GL364 kit</comment>
      <references>
        <reference>
          <reference_text>Hernandez-Castellano LE, Hernandez LL, Weaver S, Bruckmaier RM: Increased serum serotonin improves parturient calcium homeostasis in dairy cows. J Dairy Sci. 2017 Feb;100(2):1580-1587. doi: 10.3168/jds.2016-11638. Epub 2016 Dec 14.</reference_text>
          <pubmed_id>27988124</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>2150-2180</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Cobas c311/501 chemistry analyzer</comment>
      <references>
        <reference>
          <reference_text>Macdonald AGC, Bourgon SL, Palme R, Miller SP, Montanholi YR: Evaluation of blood metabolites reflects presence or absence of liver abscesses in beef cattle. Vet Rec Open. 2017 Apr 1;4(1):e000170. doi: 10.1136/vetreco-2016-000170. eCollection 2017.</reference_text>
          <pubmed_id>28890789</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>3962 +/- 443</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>3290-4070</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Membrane-immobilized enzyme with YSI 7100 MBS select biochemistry analyzer</comment>
      <references>
        <reference>
          <reference_text>Raun BM, Kristensen NB: Metabolic effects of feeding ethanol or propanol to postpartum transition Holstein cows. J Dairy Sci. 2011 May;94(5):2566-80. doi: 10.3168/jds.2010-3999.</reference_text>
          <pubmed_id>21524548</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>4013.191</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>1200 ml pomegranate peel extract/cow per day</comment>
      <references>
        <reference>
          <reference_text>M.J. Abarghuei, Y. Rouzbehan, A.Z.M Salem, M.J. Zamiri. Nitrogen balance, blood metabolites and milk fatty acid composition of dairy cows fed pomegranate-peel extract. Livestock Science (2014) 164:72-80   doi: 10.1016/j.livsci.2014.03.021</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>3807.813</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>400 ml pomegranate peel extract/cow per day</comment>
      <references>
        <reference>
          <reference_text>M.J. Abarghuei, Y. Rouzbehan, A.Z.M Salem, M.J. Zamiri. Nitrogen balance, blood metabolites and milk fatty acid composition of dairy cows fed pomegranate-peel extract. Livestock Science (2014) 164:72-80   doi: 10.1016/j.livsci.2014.03.021</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>4213.0177</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>800 ml pomegranate peel extract/cow per day</comment>
      <references>
        <reference>
          <reference_text>M.J. Abarghuei, Y. Rouzbehan, A.Z.M Salem, M.J. Zamiri. Nitrogen balance, blood metabolites and milk fatty acid composition of dairy cows fed pomegranate-peel extract. Livestock Science (2014) 164:72-80   doi: 10.1016/j.livsci.2014.03.021</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>3560-3680</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Glucose-B test kit (Wako Pure Chemical)</comment>
      <references>
        <reference>
          <reference_text>Sato H, Matsumoto M, Hanasaka S: Relations between plasma acetate, 3-hydroxybutyrate, FFA, glucose levels and energy nutrition in lactating dairy cows. J Vet Med Sci. 1999 May;61(5):447-51. doi: 10.1292/jvms.61.447.</reference_text>
          <pubmed_id>10379932</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value>2600-3870</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Glucose OSR6222 with Beckman-Olympus AU 600 chemistry analyzer</comment>
      <references>
        <reference>
          <reference_text>Liker B.,  L. Bačar-Huskić,  M. Knežević,  V. Rupić,  N. Vranešić,  Ž. Romić,  D. Grbeša,  D. Mačešić,  J. Leto,  Z. Antunović,  Ž. Krnić. 2005. Blood metabolites and haematological indices of pregnant beef cows fed rumen-protected methionine. J. Anim. Feed Sci. 14(4):625–638</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR</comment>
      <references>
        <reference>
          <reference_text>De Buck J, Shaykhutdinov R, Barkema HW, Vogel HJ: Metabolomic profiling in cattle experimentally infected with Mycobacterium avium subsp. paratuberculosis. PLoS One. 2014 Nov 5;9(11):e111872. doi: 10.1371/journal.pone.0111872. eCollection 2014.</reference_text>
          <pubmed_id>25372282</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR. Samples have been collected from 22 clinically normal, 6-12 month old Holstein–Friesian heifers and stored at -20 °C for between 2 and 15 years.</comment>
      <references>
        <reference>
          <reference_text>Trabi M, Keller MD, Johnsson NN. NMR-based metabonomics of bovine blood: an investigation into the effects of long term storage on plasma samples. Metabolomics (2013) 9:1041-1047   doi: 10.1007/s11306-013-0520-2</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Blood</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected by NMR. Samples have been collected from 24 male 17-22-month-old Charolais beef cattles.</comment>
      <references>
        <reference>
          <reference_text>Graham SF, Ruiz-Aracama A, Lommen A, Cannizzo FT, Biolatti B, Elliott CT, Mooney MH: Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations. Anal Bioanal Chem. 2012 Apr;403(2):573-82. doi: 10.1007/s00216-012-5815-z. Epub 2012 Feb 28.</reference_text>
          <pubmed_id>22370585</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Brain</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Epidermis</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Eye Lens</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Fibroblasts</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Intestine</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Kidney</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under corn stover based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under alfalfa hay based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value>80098 +/- 14629</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Liver</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Metabolomics analysis was performed using GC-MS/LC-MS in multiparous Holstein dairy cows</comment>
      <references>
        <reference>
          <reference_text>Shahzad K, Lopreiato V, Liang Y, Trevisi E, Osorio JS, Xu C, Loor JJ: Hepatic metabolomics and transcriptomics to study susceptibility to ketosis in response to prepartal nutritional management. J Anim Sci Biotechnol. 2019 Dec 18;10:96. doi: 10.1186/s40104-019-0404-z. eCollection 2019.</reference_text>
          <pubmed_id>31867104</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Longissimus Thoracis Muscle</biospecimen>
      <concentration_value>536 +/- 259</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Lung</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Mammary Gland</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under corn stover based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Mammary Gland</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>8 multiparous Chinese Holstein dairy cows fed in the Hangzhou Hangjiang Dairy Farm based on the milk production under alfalfa hay based diets. Detection used gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS) platform.</comment>
      <references>
        <reference>
          <reference_text>Sun HZ, Zhou M, Wang O, Chen Y, Liu JX, Guan LL: Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows. Bioinformatics. 2020 Apr 15;36(8):2530-2537. doi: 10.1093/bioinformatics/btz951.</reference_text>
          <pubmed_id>31873721</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>76 - 662</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Klein MS, Almstetter MF, Schlamberger G, Nurnberger N, Dettmer K, Oefner PJ, Meyer HH, Wiedemann S, Gronwald W: Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation. J Dairy Sci. 2010 Apr;93(4):1539-50. doi: 10.3168/jds.2009-2563.</reference_text>
          <pubmed_id>20338431</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>62.723</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Jensen RG: The composition of bovine milk lipids: January 1995 to December 2000. J Dairy Sci. 2002 Feb;85(2):295-350. doi: 10.3168/jds.S0022-0302(02)74079-4.</reference_text>
          <pubmed_id>11913692</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>376</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk</comment>
      <references>
        <reference>
          <reference_text>Faulkner A, Pollock HT: Changes in the concentration of metabolites in milk from cows fed on diets supplemented with soyabean oil or fatty acids. J Dairy Res. 1989 May;56(2):179-83.</reference_text>
          <pubmed_id>2760296</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Commercial, conventional whole milk</comment>
      <references>
        <reference>
          <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff, John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375-386   doi: 10.1007/s11306-009-0160-8</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>723</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk</comment>
      <references>
        <reference>
          <reference_text>Hurtaud C, Rulquin H, Verite R: Effects of graded duodenal infusions of glucose on yield and composition of milk from dairy cows. 1. Diets based on corn silage. J Dairy Sci. 1998 Dec;81(12):3239-47. doi: 10.3168/jds.S0022-0302(98)75888-6.</reference_text>
          <pubmed_id>9891269</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Detected but not quantified in conventional whole milk</comment>
      <references>
        <reference>
          <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375?386</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>540</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk</comment>
      <references>
        <reference>
          <reference_text>Hurtaud C, Lemosquet S, Rulquin H: Effect of graded duodenal infusions of glucose on yield and composition of milk from dairy cows. 2. Diets based on grass silage. J Dairy Sci. 2000 Dec;83(12):2952-62. doi: 10.3168/jds.S0022-0302(00)75195-2.</reference_text>
          <pubmed_id>11132867</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>548</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk</comment>
      <references>
        <reference>
          <reference_text>Hurtaud C, Lemosquet S, Rulquin H: Effect of graded duodenal infusions of glucose on yield and composition of milk from dairy cows. 2. Diets based on grass silage. J Dairy Sci. 2000 Dec;83(12):2952-62. doi: 10.3168/jds.S0022-0302(00)75195-2.</reference_text>
          <pubmed_id>11132867</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>340.62 +/- 65.95</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of perennial ryegrass (GRS), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>288 +/- 32</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>1% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>261 +/- 29</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>2% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>277.537 (122.116-421.857)</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Pasteurized whole milk</comment>
      <references>
        <reference>
          <reference_text>Esperanza Troyano, Mar Villamiel, Agustin Olano, Jesus Sanz, and Isabel Martinez-Castro. Monosaccharides and myo-Inositol in Commercial Milks. J. Agric. Food Chem., 1996, 44 (3), pp 815–817</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>235 +/- 49</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>3.25% milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>250 +/- 41</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Skim milk by NMR</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>80-150</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk</comment>
      <references>
        <reference>
          <reference_text>Faulkner, A., Chaiybutr, N., Peaker, M., Carrick, D. I. and Kuhn, N. J. Metabolic significance of milk glucose. J. Dairy Res. 1981, 48, 51-56</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>932.526 +/- 68.274</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>No milk type was specified in the literature. Assume it was raw milk.</comment>
      <references>
        <reference>
          <reference_text>RAJAN SHARMA YUDHISHTHIR S RAJPUT POONAM GAURAV DOGRA SUDHIR K TOMAR.  Estimation of sugars in milk by HPLC and its application in detection of adulteration of milk with soymilk. International Journal of Dairy Technology, 2009, 62(4):514-519</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>139.879 +/- 3.886</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Whole milk</comment>
      <references>
        <reference>
          <reference_text>Tommaso R.I. Cataldi, Massimiliano Angelotti, Giuliana Bianco. Determination of mono- and disaccharides in milk and milk products by high-performance anion-exchange chromatography with pulsed amperometric detection. Analytica Chimica Acta 485 (2003) 43–49</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>250 +/- 41</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Commercial skim milk</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>288 +/- 32</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Commercial 1% milk</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>261 +/- 29</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Commercial 2% milk</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>1137.903</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk, multiparous</comment>
      <references>
        <reference>
          <reference_text>Lehloenya KV, Stein DR, Allen DT, Selk GE, Jones DA, Aleman MM, Rehberger TG, Mertz KJ, Spicer LJ: Effects of feeding yeast and propionibacteria to dairy cows on milk yield and components, and reproduction*. J Anim Physiol Anim Nutr (Berl). 2008 Apr;92(2):190-202. doi: 10.1111/j.1439-0396.2007.00726.x.</reference_text>
          <pubmed_id>18336416</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>1187.859</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk, primiparous</comment>
      <references>
        <reference>
          <reference_text>Lehloenya KV, Stein DR, Allen DT, Selk GE, Jones DA, Aleman MM, Rehberger TG, Mertz KJ, Spicer LJ: Effects of feeding yeast and propionibacteria to dairy cows on milk yield and components, and reproduction*. J Anim Physiol Anim Nutr (Berl). 2008 Apr;92(2):190-202. doi: 10.1111/j.1439-0396.2007.00726.x.</reference_text>
          <pubmed_id>18336416</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>235 +/- 49</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Commercial 3.25% milk</comment>
      <references>
        <reference>
          <reference_text>Foroutan A, Guo AC, Vazquez-Fresno R, Lipfert M, Zhang L, Zheng J, Badran H, Budinski Z, Mandal R, Ametaj BN, Wishart DS: Chemical Composition of Commercial Cow's Milk. J Agric Food Chem. 2019 Apr 17. doi: 10.1021/acs.jafc.9b00204.</reference_text>
          <pubmed_id>30994344</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>387.43 +/- 91.21</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of perennial ryegrass and white clover (CLV), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Milk samples collected from 456 Danish Holstein cows </comment>
      <references>
        <reference>
          <reference_text>Buitenhuis AJ, Sundekilde UK, Poulsen NA, Bertram HC, Larsen LB, Sorensen P: Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk. J Dairy Sci. 2013 May;96(5):3285-95. doi: 10.3168/jds.2012-5914. Epub 2013 Mar 15.</reference_text>
          <pubmed_id>23497994</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <comment>Whole milk  from markets</comment>
      <references>
        <reference>
          <reference_text>Scano P, Murgia A, Pirisi FM, Caboni P: A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk. J Dairy Sci. 2014 Oct;97(10):6057-66. doi: 10.3168/jds.2014-8247. Epub 2014 Aug 6.</reference_text>
          <pubmed_id>25108860</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Milk</biospecimen>
      <concentration_value>331.24 +/- 84.17</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Raw milk metabolite measured during mid-lactation from cows fed diets consisting of total mixed ration (TMR), by 1H-NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>6310 +/- 850</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 14 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>6000 +/- 2470</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 21 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>5640 +/- 2870</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 3 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>5590 +/- 2350</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>Detected by NMR in beef muscle (longissimus dorsi) matured for 7 days.</comment>
      <references>
        <reference>
          <reference_text>S. F. Graham, T. Kennedy, O. Chevallier, A. Gordon, L. Farmer, C. Elliott, B. Moss. The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics (2010) 6:395-404   doi: 10.1007/s11306-010-0206-y</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Muscle</biospecimen>
      <concentration_value>3300</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>Kim YH, Kemp R, Samuelsson LM: Effects of dry-aging on meat quality attributes and metabolite profiles of beef loins. Meat Sci. 2016 Jan;111:168-76. doi: 10.1016/j.meatsci.2015.09.008. Epub 2015 Sep  26.</reference_text>
          <pubmed_id>26437054</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Neuron</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ovary</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Pancreas</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Placenta</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Prostate Tissue</biospecimen>
      <concentration_value/>
      <concentration_units/>
      <references>
        <reference>
          <reference_text>Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089.</reference_text>
          <pubmed_id>29140435</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>66-1138</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR</comment>
      <references>
        <reference>
          <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
          <pubmed_id>29642378</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>400</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Detected by NMR in mid-lactating primiparous Holstein cows.</comment>
      <references>
        <reference>
          <reference_text>Zhao S, Zhao J, Bu D, Sun P, Wang J, Dong Z: Metabolomics analysis reveals large effect of roughage types on rumen microbial metabolic profile in dairy cows. Lett Appl Microbiol. 2014 Jul;59(1):79-85. doi: 10.1111/lam.12247. Epub 2014 Apr  4.</reference_text>
          <pubmed_id>24617926</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>580</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (15% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>4-18</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By GC-MS</comment>
      <references>
        <reference>
          <reference_text>Raun BM, Kristensen NB: Metabolic effects of feeding ethanol or propanol to postpartum transition Holstein cows. J Dairy Sci. 2011 May;94(5):2566-80. doi: 10.3168/jds.2010-3999.</reference_text>
          <pubmed_id>21524548</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>720</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (30% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>2090</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows fed barley grains (45% of diet dry matter)</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>400</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Primiparous Holstein cows, no barley grains in diet.</comment>
      <references>
        <reference>
          <reference_text>Burim NA, Qendrim Z, Fozia S, Psychogios N, Michael JL, Dunn SM, Jianguo X, Wishart DS. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics. 2010;6(4):583-594   doi: 10.1007/s11306-010-0227-6</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>15934 +/- 11188</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>520.41 +/- 94.97</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>763.813 +/- 751.731</concentration_value>
      <concentration_units>uM</concentration_units>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>750</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (15% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>1100</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (30% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>2430</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. Daily cows fed barley grains (45% of diet dry matter) (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>520</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>By NMR. No barley grains in diet (n=8)</comment>
      <references>
        <reference>
          <reference_text>Saleem F, Ametaj BN, Bouatra S, Mandal R, Zebeli Q, Dunn SM, Wishart DS: A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci. 2012 Nov;95(11):6606-23. doi: 10.3168/jds.2012-5403. Epub 2012 Sep 7.</reference_text>
          <pubmed_id>22959937</pubmed_id>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>523 +/- 130</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (15% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>996 +/- 334</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (30% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>1806 +/- 1305</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow fed barley grains (45% of diet dry matter). </comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>549 +/- 97</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow, no barley grains in diet.</comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Ruminal Fluid</biospecimen>
      <concentration_value>549 +/- 97</concentration_value>
      <concentration_units>uM</concentration_units>
      <comment>Samples have been collected from 8 healthy primiparous Holstein cow, no barley grains in diet. Metabolite measured by NMR and GC-MS</comment>
      <references>
        <reference>
          <reference_text>Fozia Saleem, Souhaila Bouatra, An Chi Guo, Nikolaos Psychogios, Rupasri Mandal, Suzanna M. Dunn, Burim N. Ametaj, David S. Wishart. The Bovine Ruminal Fluid Metabolome. Metabolomics (2013) 9:360–378.</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Semimembranosus Muscle</biospecimen>
      <concentration_value>754 +/- 403</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
    <concentration>
      <biospecimen>Testis</biospecimen>
      <concentration_value>149 +/- 66</concentration_value>
      <concentration_units>nmol/g of tissue</concentration_units>
      <comment>By LC-MS/MS &amp; NMR</comment>
      <references>
        <reference>
          <reference_text>Aidin Foroutan, Carolyn Fitzsimmons, Rupasri Mandal, Hamed Piri‐Moghadam, Jiamin Zheng, AnChi Guo, Carin Li, Le Luo Guan and David S. Wishart. The Bovine Metabolome. Metabolites 2020, 10, 233; doi:10.3390/metabo10060233</reference_text>
          <pubmed_id/>
        </reference>
      </references>
    </concentration>
  </normal_concentrations>
  <chemspider_id>5589</chemspider_id>
  <kegg_id>C00031</kegg_id>
  <foodb_id>FDB093715</foodb_id>
  <drugbank_id/>
  <pubchem_compound_id>5793</pubchem_compound_id>
  <knapsack_id>C00001122</knapsack_id>
  <chebi_id>4167</chebi_id>
  <meta_cyc_id>D-Glucose</meta_cyc_id>
  <wikipedia_id>Glucose</wikipedia_id>
  <pdbe_id/>
  <phenol_explorer_compound_id/>
  <bigg_id/>
  <metlin_id/>
  <synthesis_reference>Li, Dalin; Ruan, Yi; Song, Wen; Wang, Yongjun.  Improved process for producing glucose.  Faming Zhuanli Shenqing Gongkai Shuomingshu  (2003),     4 pp</synthesis_reference>
  <general_references>
    <reference>
      <reference_text>Faulkner A, Pollock HT: Changes in the concentration of metabolites in milk from cows fed on diets supplemented with soyabean oil or fatty acids. J Dairy Res. 1989 May;56(2):179-83.</reference_text>
      <pubmed_id>2760296</pubmed_id>
    </reference>
    <reference>
      <reference_text>Hurtaud C, Rulquin H, Verite R: Effects of graded duodenal infusions of glucose on yield and composition of milk from dairy cows. 1. Diets based on corn silage. J Dairy Sci. 1998 Dec;81(12):3239-47. doi: 10.3168/jds.S0022-0302(98)75888-6.</reference_text>
      <pubmed_id>9891269</pubmed_id>
    </reference>
    <reference>
      <reference_text>Hurtaud C, Lemosquet S, Rulquin H: Effect of graded duodenal infusions of glucose on yield and composition of milk from dairy cows. 2. Diets based on grass silage. J Dairy Sci. 2000 Dec;83(12):2952-62. doi: 10.3168/jds.S0022-0302(00)75195-2.</reference_text>
      <pubmed_id>11132867</pubmed_id>
    </reference>
    <reference>
      <reference_text>Lehloenya KV, Stein DR, Allen DT, Selk GE, Jones DA, Aleman MM, Rehberger TG, Mertz KJ, Spicer LJ: Effects of feeding yeast and propionibacteria to dairy cows on milk yield and components, and reproduction*. J Anim Physiol Anim Nutr (Berl). 2008 Apr;92(2):190-202. doi: 10.1111/j.1439-0396.2007.00726.x.</reference_text>
      <pubmed_id>18336416</pubmed_id>
    </reference>
    <reference>
      <reference_text>Klein MS, Almstetter MF, Schlamberger G, Nurnberger N, Dettmer K, Oefner PJ, Meyer HH, Wiedemann S, Gronwald W: Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation. J Dairy Sci. 2010 Apr;93(4):1539-50. doi: 10.3168/jds.2009-2563.</reference_text>
      <pubmed_id>20338431</pubmed_id>
    </reference>
    <reference>
      <reference_text>Jensen RG: The composition of bovine milk lipids: January 1995 to December 2000. J Dairy Sci. 2002 Feb;85(2):295-350. doi: 10.3168/jds.S0022-0302(02)74079-4.</reference_text>
      <pubmed_id>11913692</pubmed_id>
    </reference>
    <reference>
      <reference_text>Buitenhuis AJ, Sundekilde UK, Poulsen NA, Bertram HC, Larsen LB, Sorensen P: Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk. J Dairy Sci. 2013 May;96(5):3285-95. doi: 10.3168/jds.2012-5914. Epub 2013 Mar 15.</reference_text>
      <pubmed_id>23497994</pubmed_id>
    </reference>
    <reference>
      <reference_text>Scano P, Murgia A, Pirisi FM, Caboni P: A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk. J Dairy Sci. 2014 Oct;97(10):6057-66. doi: 10.3168/jds.2014-8247. Epub 2014 Aug 6.</reference_text>
      <pubmed_id>25108860</pubmed_id>
    </reference>
    <reference>
      <reference_text>O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, Dong E, Mandal R, Hennessy D, McAuliffe S, Dillon P, Wishart DS, Stanton C, Ross RP: Pasture Feeding Changes the Bovine Rumen and Milk Metabolome. Metabolites. 2018 Apr 6;8(2). pii: metabo8020027. doi: 10.3390/metabo8020027.</reference_text>
      <pubmed_id>29642378</pubmed_id>
    </reference>
    <reference>
      <reference_text>Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375?386</reference_text>
    </reference>
    <reference>
      <reference_text>A. Foroutan et al. The Chemical Composition of Commercial Cow's Milk (in preparation)</reference_text>
    </reference>
  </general_references>
  <protein_associations>
    <protein>
      <protein_accession>BMDBP00131</protein_accession>
      <name>Lysosomal acid glucosylceramidase</name>
      <uniprot_id>Q2KHZ8</uniprot_id>
      <gene_name>GBA</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00165</protein_accession>
      <name>Glucose-6-phosphatase</name>
      <uniprot_id>Q29RU6</uniprot_id>
      <gene_name>G6PC</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00179</protein_accession>
      <name>Tyrosine-protein kinase</name>
      <uniprot_id>A7MB57</uniprot_id>
      <gene_name>YES1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00604</protein_accession>
      <name>Beta-1,4-galactosyltransferase 1</name>
      <uniprot_id>P08037</uniprot_id>
      <gene_name>B4GALT1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00912</protein_accession>
      <name>Hexokinase-1</name>
      <uniprot_id>P27595</uniprot_id>
      <gene_name>HK1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00913</protein_accession>
      <name>Kininogen-2</name>
      <uniprot_id>P01045</uniprot_id>
      <gene_name>KNG2</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00914</protein_accession>
      <name>Alpha-1,3-mannosyl-glycoprotein 4-beta-N-acetylglucosaminyltransferase A</name>
      <uniprot_id>O77836</uniprot_id>
      <gene_name>MGAT4A</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00915</protein_accession>
      <name>Phosphatidylinositol 3-kinase regulatory subunit alpha</name>
      <uniprot_id>P23727</uniprot_id>
      <gene_name>PIK3R1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00916</protein_accession>
      <name>AMP-activated protein kinase gamma subunit</name>
      <uniprot_id>Q4G3U3</uniprot_id>
      <gene_name>PRKAG3</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00917</protein_accession>
      <name>RAC-alpha serine/threonine-protein kinase</name>
      <uniprot_id>Q01314</uniprot_id>
      <gene_name>AKT1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP00918</protein_accession>
      <name>Kininogen-1</name>
      <uniprot_id>P01044</uniprot_id>
      <gene_name>KNG1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01304</protein_accession>
      <name>Alpha-lactalbumin</name>
      <uniprot_id>P00711</uniprot_id>
      <gene_name>LALBA</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01330</protein_accession>
      <name>Unconventional myosin-Ic</name>
      <uniprot_id>Q27966</uniprot_id>
      <gene_name>MYO1C</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01617</protein_accession>
      <name>Collectin-43</name>
      <uniprot_id>P42916</uniprot_id>
      <gene_name>CL43</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01874</protein_accession>
      <name>Sodium/myo-inositol cotransporter 2</name>
      <uniprot_id>Q3ZC26</uniprot_id>
      <gene_name>SLC5A11</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP01883</protein_accession>
      <name>Peroxisome proliferator-activated receptor gamma</name>
      <uniprot_id>O18971</uniprot_id>
      <gene_name>PPARG</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02025</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 4</name>
      <uniprot_id>Q27994</uniprot_id>
      <gene_name>SLC2A4</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02034</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 1</name>
      <uniprot_id>P27674</uniprot_id>
      <gene_name>SLC2A1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02036</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 8</name>
      <uniprot_id>P58354</uniprot_id>
      <gene_name>SLC2A8</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02044</protein_accession>
      <name>P2Y purinoceptor 14</name>
      <uniprot_id>Q3SX17</uniprot_id>
      <gene_name>P2RY14</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02051</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 12</name>
      <uniprot_id>Q5J316</uniprot_id>
      <gene_name>SLC2A12</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02056</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 3</name>
      <uniprot_id>P58352</uniprot_id>
      <gene_name>SLC2A3</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02075</protein_accession>
      <name>Solute carrier family 2, facilitated glucose transporter member 5</name>
      <uniprot_id>P58353</uniprot_id>
      <gene_name>SLC2A5</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02145</protein_accession>
      <name>Angiopoietin-related protein 4</name>
      <uniprot_id>Q2KJ51</uniprot_id>
      <gene_name>ANGPTL4</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02146</protein_accession>
      <name>Sorbin and SH3 domain containing 1</name>
      <uniprot_id>Q0VCF1</uniprot_id>
      <gene_name>SORBS1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02147</protein_accession>
      <name>Islet amyloid polypeptide</name>
      <uniprot_id>Q28207</uniprot_id>
      <gene_name>IAPP</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02149</protein_accession>
      <name>Putative sodium-glucose cotransporter</name>
      <uniprot_id>Q9TTR6</uniprot_id>
      <gene_name>sglt1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02150</protein_accession>
      <name>Chromogranin-A</name>
      <uniprot_id>P05059</uniprot_id>
      <gene_name>CHGA</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02151</protein_accession>
      <name>Solute carrier family 2 (Facilitated glucose transporter), member 3</name>
      <uniprot_id>A2VDL2</uniprot_id>
      <gene_name>SLC2A3</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02152</protein_accession>
      <name>Solute carrier family 2 (Facilitated glucose transporter), member 6</name>
      <uniprot_id>A1L502</uniprot_id>
      <gene_name>SLC2A6</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02153</protein_accession>
      <name>Glucagon</name>
      <uniprot_id>P01272</uniprot_id>
      <gene_name>GCG</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02154</protein_accession>
      <name>Solute carrier family 5 member 1</name>
      <uniprot_id>A5HNF2</uniprot_id>
      <gene_name>SLC5A1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02155</protein_accession>
      <name>Hypoxia-inducible factor 1-alpha</name>
      <uniprot_id>Q9XTA5</uniprot_id>
      <gene_name>HIF1A</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02156</protein_accession>
      <name>Multifunctional fusion protein</name>
      <uniprot_id>Q5MAC0</uniprot_id>
      <gene_name>IL1B</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02157</protein_accession>
      <name>Na+/glucose cotransporter</name>
      <uniprot_id>Q8MKB7</uniprot_id>
      <gene_name>SGLT1</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02158</protein_accession>
      <name>Sodium-dependent glucose transporter SGLT-I</name>
      <uniprot_id>Q95JG8</uniprot_id>
      <gene_name/>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02159</protein_accession>
      <name>Kruppel-like factor 15</name>
      <uniprot_id>Q6UNK6</uniprot_id>
      <gene_name/>
      <protein_type>Enzyme</protein_type>
    </protein>
    <protein>
      <protein_accession>BMDBP02911</protein_accession>
      <name>Lactase</name>
      <uniprot_id>E1BK89</uniprot_id>
      <gene_name>LCT</gene_name>
      <protein_type>Enzyme</protein_type>
    </protein>
  </protein_associations>
</metabolite>
